Merge pull request #3810 from aaaasssddf/master

fixed dimension compatibility issue for numpy

Author: shlens

tutorials/image/cifar10/cifar10.py

@@ -240,7 +240,7 @@ def inference(images):
   # local3
   with tf.variable_scope('local3') as scope:
     # Move everything into depth so we can perform a single matrix multiply.
-    reshape = tf.reshape(pool2, [images.get_shape()[0], -1])
+    reshape = tf.reshape(pool2, [images.get_shape().as_list()[0], -1])
     dim = reshape.get_shape()[1].value
     weights = _variable_with_weight_decay('weights', shape=[dim, 384],
                                           stddev=0.04, wd=0.004)